As digital video grows in popularity, brands are faced with the challenge of knowing which elements in their many videos –– created by them or by the influencers they hire — elicit the best responses.

Today, social video analytics firm Delmondo is announcing a partnership with AI/computer vision firm Uru to automatically recognize brands’ video content and generate analytics about who’s watching. This is the first such partnership for both of the New York City-based firms, and it showcases the launch of what Uru says is the first automated brand safety scanning for video.

Delmondo provides analytics for brands and publishers about the performance of their videos on Facebook, Instagram, YouTube, Twitter, Snapchat, Twitch, over-the-top TV and first-party video players.

The company’s platform can provide such info as how many females 18-34 on Facebook watched segments in its videos that showed puppies. Previously, however, the client would have manually chosen those segments and then reviewed Delmondo’s relevant audience data about those excerpts.

Now, Uru’s AI/computer vision tech can automatically scan for over 10,000 specific objects or themes by looking at the video imagery, analyzing audio content through natural language processing and parsing any text inside the video.

Delmondo CEO and founder Nick Cicero told me that no other platform can similarly tag video content in near-real time and automatically present audience data, authenticated through a social platform.

The results include not only the relatively common scanning for brand logos but for such objects/themes as sky or airplane or daytime. The analysis also pegs the video into one of the several hundred content categories established by the Interactive Advertising Bureau (IAB), such as travel or food/drink. Cicero noted that content and audience analysis can be delivered to a client within three hours of an initial video feed, which he said was an industry record.

Uru CEO and co-founder Bill Marino told me his company is in the “business of understanding what’s inside the video.”

A chain of hardware stores, for instance, might want to know how many of its created videos — or of the influencer video makers it has hired for specific campaigns — show people fixing up their kitchens, and what the audience stats were for those segments.

In addition to object/theme recognition, Uru is also launching today what it says is the first automated scanning of video content for brand safety.

Uru’s machine learning, Marino said, has acquired the ability to distinguish such content as riots, weapons, hate speech, profanity or Not Safe for Work content, as well as determine sentiment.

The brand safety tech has been in testing since September, and Marino said its accuracy is high for the most obviously recognizable content like porn, and somewhat less for more ambiguous content like bullying. For both automated video content and brand safety recognition, the companies say it’s too early yet for stats on whether they help brands or publishers improve performance.

About The Author

Barry Levine

Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.